EVEN, Philippe 
  
SEMI-AUTOMATED EDGE SEGMENT SPECIFICATION 
FOR AN INTERACTIVE MODELLING SYSTEM OF ROBOT ENVIRONMENTS 
Philippe EVEN, Anne MALAVAUD 
Atomic Energy Commission, Teleoperation and Robotics Department, 
(CEA/STR), PO Box 6, F-92265 Fontenay-Aux-Roses, France, 
Philippe.Even@cea.fr, Anne.Malavaud@cea.fr 
KEY WORDS: Modelling, Semi-automation, User interfaces, On-line, Robots. 
ABSTRACT 
Interactive methods are well suited to telerobotics purposes. Based on the super-imposition of the model on video images, 
they provide a friendly way to acquire or update the environment model from an on-board CCD camera. It is a flexible 
way to cope with a priori model inaccuracies and any possible mission incidents. Modelling time is a key requirement 
which can be fulfilled through the integration of semi-automatic assistances. This paper deals with the semi-automation 
of edge segment specification tasks. Edge segments combinations define 3-D lines or planes, which are used to orient the 
modelled objects. Their accurate specification is a tiring and time consuming task, which can not be fully automated. In 
the semi-automatic mode we set up, the operator quickly draws a line over the image. This line is automatically attracted 
towards the nearest extracted edge contour. The automatic attraction function is based on the Hough transform. This semi- 
automatic assistance has been integrated into the Pyramide interactive 3-D modelling system, which has been developed 
at CEA/STR. Evaluations on realistic sites showed its high flexibility and efficiency. 
1 INTRODUCTION 
Within the last decade, CEA/STR has developed an interactive system, called Pyramide, to acquire a 3-D model of a 
teleoperated robot environment using video images provided by an embedded CCD camera (Even and Marcé, 1988). Its 
principle consists in superimposing solid primitives on the images, and interactively adjusting their position and para- 
meters until they match the objects contours. It has been designed for on-line applications to provide computer graphics 
assistances during robotics missions. Fast acquisition and user-friendly operating mode are important requirements. In 
order to fulfil these requirements, several assistances based on image processing techniques or structural and functional 
knowledge have been integrated. A major one is a semi-automated edge segment specification assistance, which brought 
noticeable improvements. 
Pyramide provides a generic modelling module aiming at modelling any structured environment as an assembly of basic 
volumes (block, cylinder, cone, ...). 3-D features (plane, line, point, orientation) are determined from image features (edge 
segments or points) or already defined objects (planes, edges, vertices), and displayed as manipulation frames. They are 
then used to position the selected primitives in the 3-D space. For instance, the selection of the same contour on two 
oriented images defines a 3-D line used to constrain the position of one of the object edges. In order to speed up that 
process, the structural or functional knowledge on some particular environment is exploited inside specialised modules 
featuring dedicated primitives, constraints and modelling methods. In the case of a piping module, a straight pipe is 
modelled by specifying its contours in two images or more. So edge segment specification is often required as well in the 
generic module as in specialised ones. 
Careful matching of 2-D segments on image edges in manual mode is long and visually tiring. On the over hand, its full 
automation is often doomed to failure, because of poor visibility, bad scene illumination, numerous reflects on stainless 
steel surfaces, frequent occlusions, ... Therefore a semi-automated mode has been implemented. Each time the operator 
draws a segment over an image, a local edge detection function is automatically executed, and attracts the segment on the 
nearest edge found in the image. Hence only a coarse specification is required from the operator. Of course the segment 
may be attracted towards some disturbing edge close to the desired one. The operator then selects one of the segment 
ends and drags it towards the relevant edge. New edge points are thus extracted on a different image area. This is the only 
way to act on the automatic function. In case of repeated failures, the operator can come back to the manually specified 
segment with a simple undoing action. When it happens too often, the automatic function can be disabled. 
The edge detection function consists in extracting edge points inside a rectangular image area around the selected segment. 
For each point, possible edges are accumulated inside a Hough table. A vote is then performed to provide the best 
candidate. The sides of the detection area are parallel to the image borders. The distance between the initial segment and 
  
222 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B5. Amsterdam 2000. 
  
  
the @ 
shot 
initi 
desi 
This 
size 
time 
But 
spec 
mod 
perf 
The 
sele 
date 
to b 
CE, 
met 
cali 
alsc